Package teamwork :: Package agent :: Module stereotypes :: Class Stereotyper

Class Stereotyper

              Agent.Agent --+        
                            |        
RecursiveAgent.RecursiveAgent --+    
                                |    
         GoalBased.GoalBasedAgent --+
                                    |
                                   Stereotyper

Known Subclasses:

Mix-in class that supports stereotypical mental models

Nested Classes

[hide private]

Inherited from Agent.Agent: actionClass

Instance Methods

[hide private]

__copy__(self, new=None)

source code

__init__(self, name)

source code

__str__(self)
Returns a string representation of this entity

source code

__xml__(self)

source code

clusterSpace(self, granularity, weightList=None, debug=None, finish=None, interrupt=None)

source code

freezeModels(self)
Lock the model of this agent and all mental models it may have

source code

(dict:teamwork.reward.MinMaxGoal.MinMaxGoal→float)[]

generateSpace(self, granularity=10, goals=None, weightList=None, availableWeight=1.0)
Generates a space of possible goal weights for this agent

source code

hypotheticalPreCom(self, beliefs, actions, epoch=-1, debug=Debugger (0))
Returns the hypothetical model changes

source code

parse(self, element)
Extracts this agent's recursive belief structure from the given XML Element

source code

reachable(self, weightList, granularity, neighbors=None)

source code

setModel(self, model, fixed=False)
Applies the named mental model to this entity

source code

updateModel(self, actual, debug=Debugger (0))
Updates the mental model in response to the single action

source code

updateModels(self, actions, debug)
Updates the mental models in response to the given dictionary of actions

source code

weightEqual(self, weight1, weight2)

source code

Inherited from GoalBased.GoalBasedAgent: actionValue, applyGoals, expectedValue, fit, generateConstraints, getGoalTree, getGoalVector, getGoalWeight, getGoals, getNormalization, normalizeGoals, setGoalWeight, setGoals

Inherited from RecursiveAgent.RecursiveAgent: __deepcopy__, __eq__, __getitem__, __ne__, ancestry, applyChanges, applyPolicy, beliefDepth, findObservation, freeze, getActionKeys, getAllBeliefs, getBelief, getBeliefKeys, getDynamics, getEntities, getEntity, getEntityBeliefs, getNestedBelief, getObservation, getObservations, getSelfBelief, getState, getStateFeatures, hasBelief, incorporateMessage, initialStateEstimator, invalidateCache, multistep, observe, preComStateEstimator, resetHistory, saveObservations, setBelief, setEntity, setName, setObservation, setRecursiveBelief, setSelfBelief, setState, stateEstimator, step, toHTML, updateStateDict

Inherited from Agent.Agent: __cmp__, generateAllObservations, generateHistories, legalActions, legalMessages, observable, postComStateEstimator

Class Variables

[hide private]

boolean defaultModelChange = None
Class-wide default for modelChange attribute

Inherited from GoalBased.GoalBasedAgent: valueType

Instance Variables

[hide private]

dictionary model
the current stereotype that this agent is following

boolean modelChange
Flag that specifies whether this agent will change its mental models or not

dictionary of name: model pairs models
the space of possible stereotypes that can be applied to this agent

Inherited from GoalBased.GoalBasedAgent: constraints, goals, horizon

Inherited from RecursiveAgent.RecursiveAgent: dynamics, parent, relationships, state

Inherited from Agent.Agent: actions, name, omega

Method Details

[hide private]

copy(self, new=None)

source code

Overrides: Agent.Agent.__copy__

init(self, name)
(Constructor)

source code

Parameters:

name - label for this instance

Overrides: Agent.Agent.__init__

(inherited documentation)

str(self)
(Informal representation operator)

source code

Returns a string representation of this entity

Overrides: RecursiveAgent.RecursiveAgent.__str__: (inherited documentation)

xml(self)

source code

Overrides: Agent.Agent.__xml__

generateSpace(self, granularity=10, goals=None, weightList=None, availableWeight=1.0)

source code

Generates a space of possible goal weights for this agent

Parameters:

granularity (dict) - the number of positive goal weights to consider for each goal (i.e., a granularity of n will generate values of [0,1/n,2/n, ..., 1]. This is a dictionary of numbers, indexed by individual goals.
goals (teamwork.reward.MinMaxGoal.MinMaxGoal[]) - the list of goals left to consider (typically omitted, the default is the current set of goals for this agent)
weightList (dict) - the initial list of possible goal weightings, to be extended in combination with the newly generated goal weightings (typically omitted)
availableWeight (float) - the weight to be distributed across the possible goals (typically omitted, the default is 1)

Returns: (dict:teamwork.reward.MinMaxGoal.MinMaxGoal→float)[]